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Analysing Concentrating Photovoltaics Technology Through the Use of Emerging Pattern Mining

  • García-Vico, A.M. [1] ; J. Montes [1] ; J. Aguilera [1] ; Carmona, C.J. [2] ; Jesus, M.J. del [1]
    1. [1] Universidad de Jaén

      Universidad de Jaén

      Jaén, España

    2. [2] Universidad de Burgos

      Universidad de Burgos

      Burgos, España

  • Localización: International Joint Conference SOCO’16-CISIS’16-ICEUTE’16: San Sebastián, Spain, October 19th-21st, 2016 Proceedings / coord. por Manuel Graña Romay Árbol académico, José Manuel López Guede Árbol académico, Oier Etxaniz, Álvaro Herrero Cosío Árbol académico, Héctor Quintián Pardo Árbol académico, Emilio Santiago Corchado Rodríguez Árbol académico, 2017, ISBN 978-3-319-47364-2, págs. 334-344
  • Idioma: inglés
  • Texto completo no disponible (Saber más ...)
  • Resumen
    • The search of emerging patterns pursues the description of a problem through the obtaining of trends in the time, or characterisation of differences between classes or group of variables. This contribution presents an application to a real-world problem related to the photovoltaic technology through the algorithm EvAEP. Specifically, the algorithm is an evolutionary fuzzy system for emerging pattern mining applied to a problem of concentrating photovoltaic technology which is focused on the generation of electricity reducing the associated costs. Emerging pattern shave discovered relevant information for the experts when the maximum power is reached for the cells of concentrating photovoltaic.


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